Additive Manufacturing is widely applied in aerospace, automotive and marine engineering. Indeed, large-scale components are often required in these applications, such as for non-structural parts of aircraft, spare parts or small lots of cars or marine components. Fused Deposition Modelling is one of the Additive Manufacturing processes used to affordably convert digital models into mockups, prototypes, and functional parts: a slicing software converts the object’s digital model into a list of instructions for the machine. However, commercial slicing software packages often fail to accurately estimate the time required to produce models, especially when their size is significant: the errors could be up to several hours, which cannot be adequate in a real-life industrial context where production must be scheduled in a precise way. This manuscript compares the build time estimation of several commercial slicing software considering a real-life part. Furthermore, the evaluation of the manufacturing setting mainly affects the error in estimating the build time achieved through a Design of Experiment approach. The more time-impacting printing parameters have been detected, allowing fine helpful tuning to increase the accuracy of the build time in commercial slicing software. A case study included in the manuscript supports the analyses. Proper setting of the commercial slicing software can significantly improve the accuracy of the printing time.

FDM Printing Time Prediction Tuning Through a DOE Approach / Bacciaglia A.; Ceruti A.; Ciccone F.; Liverani A.. - ELETTRONICO. - (2024), pp. 3-12. (Intervento presentato al convegno 3rd International Conference on Design Tools and Methods in Industrial Engineering, ADM 2023 tenutosi a Firenze nel 2023) [10.1007/978-3-031-52075-4_1].

FDM Printing Time Prediction Tuning Through a DOE Approach

Bacciaglia A.
Primo
Data Curation
;
Ceruti A.
Secondo
Writing – Review & Editing
;
Ciccone F.
Penultimo
Membro del Collaboration Group
;
Liverani A.
Ultimo
Supervision
2024

Abstract

Additive Manufacturing is widely applied in aerospace, automotive and marine engineering. Indeed, large-scale components are often required in these applications, such as for non-structural parts of aircraft, spare parts or small lots of cars or marine components. Fused Deposition Modelling is one of the Additive Manufacturing processes used to affordably convert digital models into mockups, prototypes, and functional parts: a slicing software converts the object’s digital model into a list of instructions for the machine. However, commercial slicing software packages often fail to accurately estimate the time required to produce models, especially when their size is significant: the errors could be up to several hours, which cannot be adequate in a real-life industrial context where production must be scheduled in a precise way. This manuscript compares the build time estimation of several commercial slicing software considering a real-life part. Furthermore, the evaluation of the manufacturing setting mainly affects the error in estimating the build time achieved through a Design of Experiment approach. The more time-impacting printing parameters have been detected, allowing fine helpful tuning to increase the accuracy of the build time in commercial slicing software. A case study included in the manuscript supports the analyses. Proper setting of the commercial slicing software can significantly improve the accuracy of the printing time.
2024
Lecture Notes in Mechanical Engineering
3
12
FDM Printing Time Prediction Tuning Through a DOE Approach / Bacciaglia A.; Ceruti A.; Ciccone F.; Liverani A.. - ELETTRONICO. - (2024), pp. 3-12. (Intervento presentato al convegno 3rd International Conference on Design Tools and Methods in Industrial Engineering, ADM 2023 tenutosi a Firenze nel 2023) [10.1007/978-3-031-52075-4_1].
Bacciaglia A.; Ceruti A.; Ciccone F.; Liverani A.
File in questo prodotto:
Eventuali allegati, non sono esposti

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/964574
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? ND
social impact